Pith. sign in

Paper Citation Record · LEDGER

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation

As of 13 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2411.13942.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.13942 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:47:25.980990Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

  • verified exact0
  • verified fuzzy14
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 789caaca-9997-4832-8bbb-2c436b748e77 · outbound

This paper cites Kinematic multi-robot manipulation with no communication using force feedback,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation Kinematic multi-robot manipulation with no communication using force feedback,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.294501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.904194Z digest=sha256:9aa7425cbc33dbf5a4c0a721a185e4aa7a17646b4bca17d374eb5c8506d3f46d

Observation f7de3ef0-a85a-48ed-a59a-56740fd77c70 · outbound

This paper cites Cooperative manipulation exploiting only implicit communication,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation Cooperative manipulation exploiting only implicit communication,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.271285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.910771Z digest=sha256:c8d37b1a624e66d342f4b9ed9ab26c4d5af9609b13ba4103685f36c7b6911711

Observation 5ab3159b-9c0a-46e7-85fe-25f6620c4a34 · outbound

This paper cites A collaborative control method of dual-arm robots based on deep reinforcement learning,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation A collaborative control method of dual-arm robots based on deep reinforcement learning,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.253626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.915343Z digest=sha256:f99543e5ff4e509fe0d2b8383ed798c58c77c473fd031c717253372ef16042d1

Observation 5c19af7e-cb21-488f-b086-2f4e67d2fac1 · outbound

This paper cites The surprising effectiveness of PPO in cooperative multi-agent games,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation The surprising effectiveness of PPO in cooperative multi-agent games,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.233231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.920020Z digest=sha256:051896b6f769ada4993c2c1733474295feccc36762e1b71687cd01e6147cea5f

Observation 97cb0968-9f59-4a86-82bf-734091968e46 · outbound

This paper cites Occlusion-based cooperative transport with a swarm of miniature mobile robots,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation Occlusion-based cooperative transport with a swarm of miniature mobile robots,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T15:47:25.926621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:47:25.926621Z digest=sha256:b52257e54b1014ecf0d9bb5d3161a381eadba0a1a8fd4c59cef8e812b4f9c3ef

Observation b809b3f2-87ea-46b2-be33-9fa39b22124e · outbound

This paper cites Deep reinforcement learning of event-triggered communication and consensus-based control for distributed cooperative transport,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation Deep reinforcement learning of event-triggered communication and consensus-based control for distributed cooperative transport,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.203070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.932003Z digest=sha256:5936a8f6039386952c1af835e33a7e53ba8e6bdfa77debe450eb1bb54c0c82ce

Observation 860df8f4-9058-4df8-91d1-49339ccb94c1 · outbound

This paper cites Cooperative object trans- portation by multiple humanoid robots,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation Cooperative object trans- portation by multiple humanoid robots,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.178114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.937837Z digest=sha256:1a65e0a71e026a7859bf1c202c7bff7902a2b71c9e59d10d732e43baf32c7e7e

Observation 64ea92d6-e584-40ef-9643-035ea7c959f6 · outbound

This paper cites The need for combining implicit and explicit communication in cooperative robotic systems,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation The need for combining implicit and explicit communication in cooperative robotic systems,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.155575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.943275Z digest=sha256:0eda720861bd95ba9fe1f5aacd449d3b1d7ab990f9d9875e8d32907a579016b1

Observation c2434d34-404d-44e6-b7a5-8c5442b8a8dc · outbound

This paper cites Implicit and explicit communication in decentralized control,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation Implicit and explicit communication in decentralized control,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.137649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.948173Z digest=sha256:13ba01f2b54979bf1d5fed20391b851aa51484858d5308350659408af388f4e1

Observation 0c14723d-ff44-4835-b6c4-ce6703021a19 · outbound

This paper cites How can we understand multi-robot systems? a user study to compare implicit and explicit communication modalities,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation How can we understand multi-robot systems? a user study to compare implicit and explicit communication modalities,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.116824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.952507Z digest=sha256:65bdcf13adfc98207a286453575875d0848ba3f9a97040670282c07bc9641bb7

Observation 83aaf3c3-af25-4ec9-82f9-02e0cf591639 · outbound

This paper cites A review of safe reinforcement learning: Methods, theory and applications,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation A review of safe reinforcement learning: Methods, theory and applications,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.098578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.957130Z digest=sha256:a44fcec6468d98dbd6275b31a77252575616f94e7e8a6a5f4652d982acd22694

Observation e768dd5f-94b6-4c60-8440-9a0923b559d8 · outbound

This paper cites Multi-agent deep reinforcement learning for multi-robot applications: A survey,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation Multi-agent deep reinforcement learning for multi-robot applications: A survey,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.082538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.962986Z digest=sha256:912b77fa6db8f32f7a72ba93e67d22ecb14f75555e96b650d3aac7254253339c

Observation f37560b3-5590-4cc2-9813-35759e2e49f9 · outbound

This paper cites Decentralized multi-agent reinforcement learning with global state prediction,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation Decentralized multi-agent reinforcement learning with global state prediction,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.064887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.967223Z digest=sha256:dc5381b9356bb98c70818c10227bc506ae09982539d823dcfed7f444af571ce6

Observation 8fde9ae5-d51f-4c31-a04c-96ad960a4962 · outbound

This paper cites Asymmetric actor critic for image-based robot learning,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation Asymmetric actor critic for image-based robot learning,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.048317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.975861Z digest=sha256:abd28ab841fdee85291b3809ccd806f2e5b85454a7ec9b69dab322daa2c6715e

Observation 95083835-d45f-4ddf-b810-f608897affb1 · outbound

This paper cites Towards closing the sim-to-real gap in collaborative multi-robot deep rein- forcement learning,.

Cooperative Grasping and Transportation using Multi-agent Reinforcement Learning with Ternary Force Representation Towards closing the sim-to-real gap in collaborative multi-robot deep rein- forcement learning,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:47:26.032686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T15:47:25.980990Z digest=sha256:78fa4ad2e7e09a13df50255b87f89661d48376d5329c306ea8fb0f063ad688e8

Pith citing papers

No inbound Pith citation observations are available.